Lantern Pharma recognizes that the high cost and low success rates in oncology drug development largely stem from the inability to appropriately stratify patient populations prior to enrollment, and also from the inability to fully elucidate mechanisms of action that can suggest potent therapy combinations. Our approach, which leverages our RADR™ platform helps to provide rapid, meaningful insight to both of these central problems in oncology.

Lantern is focused on accelerating personalized cancer therapy development through the use of AI and genomic-based patient stratification.

Oncology drug development is time consuming, costly and high risk, with rates of a successful outcome (drug approval) being very low. This is a perfect problem area for the application of machine learning and Artificial Intelligence.

~3.4%

Success Rate of Oncology Drugs
from 2001 – 2015

$2+ Billion

Average Cost Per
Oncology Drug

17,368

Oncology Trials Conducted
2001-2015

2%

Success Rate Doubled for Trials that Included
Patient Stratification at the Beginning of the Trial

7%

Of Oncology Trials Utilized a Biomarker*​

Our Approach

Lantern Pharma embraces emerging technologies that can help transform the pace and insight of oncology drug development. We have applied Artificial Intelligence (AI) and machine learning techniques and methods that have been robustly tested in other industries, and are applying these to solve central problems in cancer therapy:

– the accurate stratification of patient populations into responders and non-responders which helps to de-risk and streamline clinical trials, and

– clarifying the potential mechanism of action of drugs, which can help to uncover potential combinations and improve molecular targeting of the specific cancer type.

We believe that both of these central problems are exponentially improved through the application of AI, which helps to increase the probability of successful FDA approval and ultimately reduce overall costs associated with cancer drug development.

Launched in 2014, Lantern developed its own proprietary AI-based platform, Response Algorithm for Drug Positioning and Rescue – RADR™.

We believe that both of these central problems are exponentially improved through the application of AI, which helps to increase the probability of a successful FDA approvaland drastically reduce overall costs associated with cancer drug development.

Lantern Pharma has implemented a new business model focused around in-licensing promising but failed or abandoned oncology compounds, and then out-licensing or selling them to biotech and pharma companies after revitalizing or rescuing the compound.

We are actively working on two promising targets, LP-184 and LP-300, that are in our pipeline.